| Title |
Magneto-Electric Nano-Particles for Non-Invasive Brain Stimulation
|
|---|---|
| Published in |
PLOS ONE, September 2012
|
| DOI | 10.1371/journal.pone.0044040 |
| Pubmed ID | |
| Authors |
Kun Yue, Rakesh Guduru, Jeongmin Hong, Ping Liang, Madhavan Nair, Sakhrat Khizroev |
| Abstract |
This paper for the first time discusses a computational study of using magneto-electric (ME) nanoparticles to artificially stimulate the neural activity deep in the brain. The new technology provides a unique way to couple electric signals in the neural network to the magnetic dipoles in the nanoparticles with the purpose to enable a non-invasive approach. Simulations of the effect of ME nanoparticles for non-invasively stimulating the brain of a patient with Parkinson's Disease to bring the pulsed sequences of the electric field to the levels comparable to those of healthy people show that the optimized values for the concentration of the 20-nm nanoparticles (with the magneto-electric (ME) coefficient of 100 V cm(-1) Oe(-1) in the aqueous solution) is 3 × 10(6) particles/cc, and the frequency of the externally applied 300-Oe magnetic field is 80 Hz. |
X Demographics
The data shown below were collected from the profiles of 22 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 14% |
| United Kingdom | 2 | 9% |
| India | 2 | 9% |
| Germany | 1 | 5% |
| Australia | 1 | 5% |
| Unknown | 13 | 59% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 18 | 82% |
| Scientists | 3 | 14% |
| Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 148 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| India | 1 | <1% |
| Colombia | 1 | <1% |
| Germany | 1 | <1% |
| Unknown | 142 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 40 | 27% |
| Researcher | 21 | 14% |
| Student > Master | 18 | 12% |
| Student > Bachelor | 15 | 10% |
| Student > Doctoral Student | 12 | 8% |
| Other | 14 | 9% |
| Unknown | 28 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 32 | 22% |
| Materials Science | 13 | 9% |
| Physics and Astronomy | 11 | 7% |
| Neuroscience | 10 | 7% |
| Medicine and Dentistry | 9 | 6% |
| Other | 38 | 26% |
| Unknown | 35 | 24% |